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Title: INTEGRATING MOLECULAR APPROACHES WITH QTL TO IDENTIFY POSITIONAL CANDIDATE GENES

Author
item Liu, Hsiao Ching
item Cheng, Hans

Submitted to: World Congress of Genetics Applied in Livestock Production
Publication Type: Proceedings
Publication Acceptance Date: 8/17/2002
Publication Date: 8/19/2002
Citation: Liu, H., Cheng, H.H. 2002. Integrating molecular approaches with QTL to identify positional candidate genes. World Congress of Genetics Applied in Livestock Production. p. 40-49.

Interpretive Summary:

Technical Abstract: Recent advances in genomics have made it possible for more precise selection of high merit animals. In the past decade, great progress has been made to identify quantitative trait loci (QTL), which are specific regions of the genome that influence traits and act together to produce continuous variation. In order to identify and map QTL efficiently, genetic markers located throughout the genome are systematically examined to see if alleles explain some of the phenotypic observed variation. The power to identify and resolve a particular QTL is dependent on the size of the resource population and the magnitude of the allele substitution effect. This fact implies that the trait has been accurately measured. Unfortunately, environmental and other non-genetic factors can make this task very difficult. Furthermore for disease, which is not a continuous trait but rather a binary one, this problem is even worse. Thus, high resolution mapping of QTL and ultimately the cloning of the causative genes for disease resistance or other traits that are poorly measured will be an exceedingly difficult undertaking using a pure genetics approach. For these reasons and others, we were motivated to look for other methods to fine map and identify position candidate genes for our previously identified QTL that confer resistance to Marek's disease (MD). In this paper, we discuss current progress of identifying causative genes in MD resistance QTL by two molecular methods (i.e., DNA microarrays and two-hybrid screens) with genetic mapping.